sustainability
Article
A Scenario Analysis of Solar Photovoltaic Grid Parity in the
Maldives: The Case of Malahini Resort
Tae Yong Jung 1, Donghun Kim 1,*, Jongwoo Moon 2 and SeoKyung Lim
1
1 Graduate School of International Studies, Yonsei University,
Seoul 03722, Korea;
[email protected] (T.Y.J.);
[email protected] (S.L.)
2 Research Center for Global Sustainability, Institute for Global
Engagement & Empowerment, Yonsei University, Seoul 03722,
Korea;
[email protected]
* Correspondence:
[email protected]; Tel.: +82-2-2123-6287
Received: 10 October 2018; Accepted: 2 November 2018; Published: 5
November 2018
Abstract: The Maldives, one of the Small Island Developing States
(SIDS) with great solar potential, is keen to promote renewable
energy systems to reduce its heavy reliance on imported diesel for
power generation. However, adopting renewable energy systems is
still burdensome for the Maldives not only because of its high
initial costs and insufficient financial resources but also because
of a lack of understanding about whether the deployment of a
renewable system is economically feasible. Therefore, the concept
of grid parity is explored as an important concept in this paper to
examine the possible timeframe for reaching it. A distinctive
feature of the paper is that the paper used actual cost and
technical information to analyze the levelized cost of energy
(LCOEs) of the independent renewable system in a remote island and
examined its timeframe for reaching the grid parity condition.
Based on economic and technical information from a project for
replacing existing diesel generator to photovoltaic (PV) with
energy storage system (ESS) in Kuda Bandos Island in the Maldives,
the paper considers three different system configurations and
evaluates which configuration could result in the most optimal
off-grid energy systems in this remote island. With sensitivity
analysis on various uncertainties, the paper shows the range of the
levelized costs of energy and the periods required for reaching
grid parity for deploying solar photovoltaics and ESSs in Kuda
Bandos Island, Maldives. The result indicates that the photovoltaic
system is an economically feasible option for the resort, and that
grid parity can be reached within the project lifetime. However,
the result shows that the use of advanced ESSs is still an
expensive option and would not be economically reasonable.
Keywords: levelized cost of energy; photovoltaic with energy
storage system; HOMER simulation; LCOE comparison; sensitivity
analysis
1. Introduction
In most remote islands, centralized generation of electricity is
nearly impossible due to their unique conditions, and it makes
diesel generation the primary source for power generation. High
dependence on diesel price puts a huge economic and environmental
burden on Small Island Developing States (SIDS). Reducing heavy
reliance on imported diesel for power generation has been an
important agenda for SIDS. This challenge has been encouraging SIDS
to increase the deployment of renewable energy systems [1]. The
recent technology development provides opportunities for the
Maldives to deploy more renewable energy systems by reducing the
costs of solar photovoltaics (PV) with or without energy storage
systems (ESS) as well as increasing their efficiencies [2].
However, adopting renewable energy systems is still burdensome for
the Maldives because of its initial costs and insufficient
financial resources. Also, the countries lack understanding about
whether a renewable system is an economically feasible option
compared to conventional energy systems. Since the countries
Sustainability 2018, 10, 4045; doi:10.3390/su10114045
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Sustainability 2018, 10, 4045 2 of 14
have limited financial resources and capacity, the economic
feasibility is inevitably an important factor for the selection of
energy systems. Therefore, achieving grid parity where the cost of
renewables becomes the same or less than that of conventional
sources is an important milestone for the successful diffusion of
renewables in SIDS.
Reducing high diesel dependence and adopting renewable systems are
also an important national agenda for the Maldives, one of the
SIDS. The Maldives is in the Indian Ocean and is composed of more
than 1000 islands. Due to its location in tropical zones, the
Maldives has a high potential for solar systems. The country
reached 100% electrification rate, but the dominant system is still
off-grid diesel generation. The Maldives has established an
ambitious target of achieving 100% renewable energy by 2020 in 2009
and encouraged the deployment of renewable systems [3]. However,
the pace of the deployment of renewable systems has been slow, and
only 1.28% of electricity generated is provided by renewables
[4].
The paper examines the possible timeframe for reaching grid parity
in a SIDS country from the case project of replacing an existing
diesel generator to photovoltaic power generation with ESS in a
resort on Kuda Bandos Island, Maldives. Kuda Bandos Island is
located near Male, the capital of the Maldives. The main economic
activity of the island is tourism, so the resort on the island has
demands for establishing a sustainable energy system. Also, this
small island is remote from other islands, and the resort is the
only demand source for energy. Thus, both the reliability and
economic feasibility of the energy system are important. The
project is funded by the Korea Institute of Energy Technology
Evaluation and Planning and the Ministry of Trade, Industry, and
Energy of the Republic of Korea. The purpose of the project is to
replace the existing diesel generator to PV with ESS and diesel
generator. The project implements the installation of PV 290 kW
with Power Conversion System (PCS) 295 kW, 728 kWh Lithium battery
and 250 kWh Vanadium Redox Flow Battery (VRFB). The objective of
the project is to develop advanced VRFB and implement the
independent renewable system on the island. Thus, the paper tests
the system’s technical feasibility and compares levelized cost of
energy (LCOEs) of three different systems, which are existing
diesel generation, solar photovoltaic systems with diesel
generators, and solar photovoltaic systems with ESSs based on the
information given from the resort and the companies providing
system components. The study uses costs, such as logistics,
technology, construction, and operations costs, and system
specifications from the case project. Since the project site is a
remote island and requires a self-sufficient energy system, the
project contains additional issues, such as including logistics
costs and operations and maintenance issues. Thus, the concept of
grid parity would be applied to the comparison among LCOEs of
feasible options. The study examines the timeframe for reaching
grid parity for those renewable systems compared to the existing
diesel generation. Examining LCOEs of different system settings,
including ESS, and their timeframe for reaching grid parity, can
contribute to accelerating deployment of renewable systems in the
Maldives as well as other SIDS countries. Furthermore, the results
can provide further implications to other islands in the Maldives,
those have similar characteristics, such as remote island and a
self-sufficient diesel generation, to the case projects.
Literature Review
In the literature, various papers studied the economic and
technical feasibility of sustainable energy systems in developing
countries and SIDS. The objectives of the studies were to find the
optimal independent renewable system and demonstrate the economic
and financial feasibility of the selected system. (Jung et al.
(2017) [5]; Ali et al. (2018) [6]; and Kaldellis et al. (2009) [7])
Jung et al. (2017) and Ali et al. (2018) both examined technical
and economic feasibilities of independent PV systems on the islands
of the Maldives by Hybrid Optimization of Multiple Electric
Renewables (HOMER) simulations and demonstrated that the PV system
is a feasible option to replace the diesel generation of the small
islands in the Maldives. In addition, Kalidellis et al. (2009)
found the optimal PV-ESS system configuration, as Jung et al.
(2017) did, for small remote islands and conducted a cost-benefit
analysis. The study also confirmed that the optimal renewable
system with ESS can be considered
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as an effective option for solving electrification issues on remote
islands, especially located in high and medium-high solar potential
regions [7]. Though those studies demonstrated the technical and
economic feasibility of the independent renewable systems, those
analyses limitedly consider the timeframe for reaching grid parity
condition of renewable systems. Therefore, the analysis of the
paper can contribute to providing additional information when the
grid parity condition of independent renewable systems can be
reached in remote islands.
Moreover, the optimal selection and the management of renewable
systems are essential parts for understanding economic feasibility
of the renewable systems. In particular, the recent progress in
computational simulation capacity allowed the introduction of the
advanced methodologies in achieving optimal management of renewable
systems with ESSs. Though this paper analyzes based on a project
with a pre-determined renewable system configuration, Rangel et al.
(2018) presented a methodology for choosing an optimal size, type,
and site of ESS. The purpose of the study was to obtain the optimal
charge and discharge strategy and find the best cost option [8].
Ghanaatian and Lotfifard (2018) proposed a method for the optimal
control of the flywheel ESS by using a tube-based Model Predictive
Control (MPC) model. The study included uncertainties and external
disturbances in the model and conducted simulations to show the
effectiveness of the model [9]. Li and Hennessy (2013) conducted a
study to reduce grid dependence of midsize European town by
adopting a large-scale PV, Wind, and VRFB. The study targeted to
reduce grid dependence, grid purchase, and spilled wind lost and
achieve shorter payback periods for the ESS. By considering
different size of VRB-ESS, the study found the optimal size and
technical specification of ESS that satisfies the objectives [10].
These studies were to find the optimal selection and management of
the battery system that satisfy the optimal operation and the
reliability of the renewable system. In addition, the advanced
methodologies are presented for the management of multiple micro
grid systems. Tavakoli et al. (2018) proposed a way to find an
optimal management system of battery energy for the commercial
building microgrid using a linear optimization programming with the
Conditional Value at Risk (CVaR). This approach considers
maximizing the management of microgrid photovoltaic system and
battery energy while reducing key uncertainties, such as
electricity price and power generation, in operating photovoltaic
energy system with battery. It not only improves the efficient use
of renewable energy system but also enhances the resilience of the
commercial microgrid [11]. Marzband et al. (2018a) and Marzband et
al. (2018b) demonstrated a smart Transactive Energy (TE) framework
that established a coalition of multiple home microgrids and found
an optimal resource management and profit sharing among the
participants [12,13]. Marzband et al. (2018a) showed a smart TE
framework that builds a coalition of multiple home microgrids and
found an optimal way to achieve fair allocation of coalition
profit. The study used a multi-stage stochastic programming based
on artificial bee colony (MSSP-ABC) algorithm to simulate the
formation of possible coalitions and find a “fair” distribution of
profits. The simulation result demonstrated that the coalition
encourages the participation of home microgrid owners and consumers
in the deregulated market and contributes to mitigating electric
load fluctuations [12]. Marzband et al. (2018b) used improved
optimization techniques to solve the non-linear and non-convex
Market Operator Transactive Energy (MO-TE) structure issue. The
method proposed by the study was used to find the home microgrids’
optimal electricity and thermal resources and maximize home
microgrids owners’ profits. This approach enables to find the
optimal timing for home microgrids owners to exchange electricity
and provides a chance to reduce the exploitation cost of home
microgrids owners [13]. However, the case project used in this
paper is a resort in a remote island with no grid connections to
other islands, and the resort operates its self-sufficient energy
system. Also, the pre-determined renewable system design was
implemented in the resort. Thus, these advanced methodologies for
optimal management of multiple home-grid systems as well as the
selection of ESS are hard to be implemented in this case.
Along with feasibility studies of on-grid and off-grid renewable
energy systems, various research has been undertaken on grid parity
analysis. To compare the different types of energy technologies,
LCOE calculation method is widely used in the grid party analysis.
In the early 2010s, the studies
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showed that a solar PV system showed a great potential to be a
feasible option in the future but reaching grid parity condition
needed much more time. (Branker et al. (2011) [14]; Yang (2010)
[15]; Lund (2011) [16]) However, the continued technological
development made the on-grid and off-grid solar PV systems more
attractive options, and the recent studies expected shorter
timeframes for reaching grid parity of PV systems. Though the
recent studies found that both off-grid and on-grid solar systems
are still expensive options for developing countries (Baurzhan and
Jenkins (2016) [17]; Zou et al. (2017) [18]), many studies found
the grid parity of solar PV systems can be reached in countries
within the next few decades. For instance, Zou et al. (2017) and
Mundada et al. (2016) studied whether the off-grid PV systems can
reach the grid parity condition in China and the US Zou et al.
(2017) found optimal solar PV systems in five different Chinese
cities and applied learning curves for calculating LCOEs. It found
that the grid parity condition of off-grid PV systems in those
Chinese cities can be reached in between about 2026 and 2050 [18].
Mundada et al. (2016) chose a residential sector in Houston, MI
with an unfavorable environment for solar systems as a case study
and calculated LCOE of off-grid PV with ESSs and combined heat and
power (CHP) systems. The study showed that LCOEs of the hybrid
system are lower than grid costs in many cases and argued that the
hybrid system can be developed further in the US in the near future
[19]. Moreover, there has been in-depth studies which included
uncertainties in calculating LCOEs of PV systems. (Biondi and
Moretto (2015) [20]; and Said et al. (2015) [21]) Biondi and
Moretto (2015) examined solar grid parity in Italy by using a real
option approach. The study evaluated uncertainties, such as energy
prices and PV module costs, and demonstrated how those
uncertainties affect the PV market in Italy. It showed that PV
systems seem to achieve grid parity soon thanks to relatively high
electricity tariffs and good solar radiation, but the uncertainties
may delay grid parity condition in Italy for several years [20].
Said et al. (2015) presented an improved modeling of LCOE that used
the effective lifetime of different types of PV technologies and
different environmental or technical conditions. The study included
the input data’s uncertainties in the analysis and examined whether
PV technologies reached grid parity in Egypt. It found the use of
the effective lifetime affects LCOE and the total electricity
generation during the lifetime [21].
Various studies on the levelized cost of energy are conducted on
comparing LCOEs of different technologies in national level and on
comparing LCOEs of grid-connected renewable systems to other
conventional energy systems. However, in the countries composed of
many islands, such as the Maldives, the grid connection among
systems is nearly impossible, and the deployment of independent
renewable systems have additional risk factors. This paper uses
actual technology, logistics, construction, and operations costs
from the project. Also, the paper applies the concept of the grid
parity to the project in a remote island in the Maldives where the
central grid system cannot be established. The findings from the
paper can be further applied to other remote islands. Moreover, the
paper conducts sensitivity analysis on key risk factors, such as
changes in discount rate and diesel price, to examine how the
external risk factors can affect the economic feasibilities and the
grid parity conditions of renewable energy systems in the
Maldives.
2. Materials and Methods
2.1. System Design and Optimization
Prior to examining the LCOEs of energy systems and the grid parity
timeframe, HOMER software version 3.12 (HOMER Energy, Boulder, CO,
USA) is used to find the optimal system configurations. HOMER
software is a powerful tool developed by US National Renewable
Energy Laboratory that simulates a viable system for all possible
combinations of different energy systems based on their technical
and economic merit [22]. HOMER can model grid-connected as well as
off-grid power systems comprising any combination of wind turbines,
PV arrays, fuel cells, small hydropower, biomass, converter,
batteries, and conventional generators [23]. The simulated systems
are sorted and filtered based on the criteria the user determines.
Next, HOMER allows analysts to conduct sensitivity
Sustainability 2018, 10, 4045 5 of 14
analyses and to examine the impacts of uncertainty and changes in
input variables. This energy modeling software simulates multiple
system combinations based on input variables such as monthly load,
discount rate, and system costs and finds the optimal system
designs, satisfying the technical constraints at the lowest net
present cost [24]. The main objective of the HOMER simulation is to
evaluate the economic and technical feasibility of renewable energy
systems to be installed in a specific location based on given
information of equipment and energy resource availability.
The simulation results show that three system configurations were
found to be viable designs based on the input variables we entered,
as shown in Figure 1. The system I represents a system design that
uses only the existing diesel generator. System II represents a
system configuration in which PV and diesel generators are used
simultaneously, and System III is composed of PV, ESS and diesel
generators.
Sustainability 2018, 10, x FOR PEER REVIEW 5 of 14
to be installed in a specific location based on given information
of equipment and energy resource availability.
The simulation results show that three system configurations were
found to be viable designs based on the input variables we entered,
as shown in Figure 1. The system I represents a system design that
uses only the existing diesel generator. System II represents a
system configuration in which PV and diesel generators are used
simultaneously, and System III is composed of PV, ESS and diesel
generators.
System I System II System III
Source: HOMER Software
2.2. Site Specification and Load Patterns
This study is conducted to replace existing diesel generators with
either PV-only or PV with ESS in the Malahini Kuda Bandos resort
located on Kuda Bandos Island, Maldives. The Malahini Kuda Bandos
resort is the only resort in this small island, and the resort is
self-satisfying its electric loads from a diesel generator. The
resort has three diesel generators. However, operating one diesel
generator at a time meets the electric loads of the resort. One of
the two other diesel generators has to be operated manually if the
electric load exceeds 500 kW. This PV-ESS project was implemented
to eliminate the inconvenience of turning on diesel generators
manually.
The Maldives is hot and sunny all throughout the year, with average
temperatures of 23 to 31 degrees Celsius. The high season falls
between December and March, and the monsoon runs from May to
October [25]. Despite fluctuations in weather condition, the
Malahini Kuda Bandos resort has a constant and stable electric load
throughout the year. Its monthly average of electric loads falls
between 303.76 kW and 338.57 kW.
2.3. Assumptions and System Components
This paper assesses the feasibility of two new technical options
for replacing diesel generators operating at Kuda Bandos Island
with either PV-only or PV-ESS. The capacity of PV is 290 kW. The
PCS that stores the power produced by Solar PV in the ESS system is
295 kW. There are also two types of ESSs included in this project:
a 728 kW Lithium-Ion Battery (LIB) type and a 250 kW VRFB
type.
In addition to the assumptions of system components, various
financial assumptions are considered. The debt-to-equity ratio is
assumed to be 70:30 [26]. The rate of return for equity is assumed
to be nominal at 13.5%, and the debt rate is assumed to be 8.5%.
The inflation rate is set as 2.2%, which is an average rate of the
Maldives between 2013 and 2017 [27]. Based on these assumptions,
the real discount rate is set as 7.8%. The debt repayment period is
set at 7 years, and the grace period is given as 1 year during the
construction period. Operation and Maintenance (O&M) costs are
assumed to be 2% of the total system cost, and the O&M costs
are expected to rise at the same rate as the annual inflation rate.
In terms of electricity generation, electricity generation from
solar is assumed to decrease by 0.5% per year as solar panel
performance declines, and diesel
Figure 1. System Configuration.
2.2. Site Specification and Load Patterns
This study is conducted to replace existing diesel generators with
either PV-only or PV with ESS in the Malahini Kuda Bandos resort
located on Kuda Bandos Island, Maldives. The Malahini Kuda Bandos
resort is the only resort in this small island, and the resort is
self-satisfying its electric loads from a diesel generator. The
resort has three diesel generators. However, operating one diesel
generator at a time meets the electric loads of the resort. One of
the two other diesel generators has to be operated manually if the
electric load exceeds 500 kW. This PV-ESS project was implemented
to eliminate the inconvenience of turning on diesel generators
manually.
The Maldives is hot and sunny all throughout the year, with average
temperatures of 23 to 31 degrees Celsius. The high season falls
between December and March, and the monsoon runs from May to
October [25]. Despite fluctuations in weather condition, the
Malahini Kuda Bandos resort has a constant and stable electric load
throughout the year. Its monthly average of electric loads falls
between 303.76 kW and 338.57 kW.
2.3. Assumptions and System Components
This paper assesses the feasibility of two new technical options
for replacing diesel generators operating at Kuda Bandos Island
with either PV-only or PV-ESS. The capacity of PV is 290 kW. The
PCS that stores the power produced by Solar PV in the ESS system is
295 kW. There are also two types of ESSs included in this project:
a 728 kW Lithium-Ion Battery (LIB) type and a 250 kW VRFB
type.
In addition to the assumptions of system components, various
financial assumptions are considered. The debt-to-equity ratio is
assumed to be 70:30 [26]. The rate of return for equity is assumed
to be nominal at 13.5%, and the debt rate is assumed to be 8.5%.
The inflation rate is set as 2.2%, which is an average rate of the
Maldives between 2013 and 2017 [27]. Based on these assumptions,
the real discount rate is set as 7.8%. The debt repayment period is
set at 7 years, and the grace period is
Sustainability 2018, 10, 4045 6 of 14
given as 1 year during the construction period. Operation and
Maintenance (O&M) costs are assumed to be 2% of the total
system cost, and the O&M costs are expected to rise at the same
rate as the annual inflation rate. In terms of electricity
generation, electricity generation from solar is assumed to
decrease by 0.5% per year as solar panel performance declines, and
diesel consumption per liter is calculated as electricity generated
by diesel (kWh) times L/kWh. We also assume that diesel prices are
set at $1.06/L [28], which is equal to the world average, and we
assume that annual diesel price rises every year at 2.2%, which is
equivalent to the inflation rate of the Maldives.
Based on this input data, the technical simulation shows the three
possible system configurations at the Kuda Bandos Island. The
possible system configurations are shown in Table 1. The base
system configuration is a diesel-only system that uses the existing
diesel generator already in operation at the resort (System I).
Another possibility is to use the existing diesel generator and 290
kW PV together (System II), and the other option is to supply
electricity to the resort using the existing diesel generator, 290
kW PV, and two types –LIB and VRFB of ESS (System III).
Table 1. System Configuration.
System PV PCS ESS Diesel
System I - - - 648 kW System II 290 kW 295 kW - 648 kW System III
290 kW 295 kW 978 kWh 648 kW
According to optimizations and simulations, in both System II and
System III, PV provides approximately 472,428 kWh for the first
year and accounts for 17.1% of electricity generated from the
entire system. As solar performance degrades 0.5% annually, the
remaining amount of electricity required will be covered by
additionally using diesel generator. The technical information
indicates that the ESS is used to avoid the occurrence of capacity
shortage and unmet electric load and reduce excess electricity.
Without an ESS, 80,525 kWh (2.92% of total electricity generation)
of electricity is considered to be excess electricity every
year.
3. Results
3.1. LCOE and Grid Parity
To find the grid parity, this study calculated yearly LCOEs based
on the technical information as well as financial assumptions. The
LCOE methodology, which is the unit cost of the energy generated by
a system over its lifetime is abstracted from reality and is used
as a benchmarking or ranking tool to evaluate the
cost-effectiveness of other energy generation technologies [29].
The LCOE method is useful in that it allows fair and direct
comparison of different electricity generation technologies [30].
Because photovoltaic and ESSs require huge initial capital
investments, both System II and System III start with very high
LCOEs of 1.08 and 0.49, respectively, as shown in Figure 2. Also,
the debt interests and repayments occurred in the first 7 years
make their LCOEs higher. As the system continues to generate more
electricity, LCOEs continues to decrease. The study assumed the
real diesel price to be fixed, LCOE of System I stays at $0.3208
per kWh. According to the study, LCOE of System II (PV + Diesel)
reaches grid parity in 5.77 years (between 2022 and 2023).
Afterward, it continues to decrease and has LCOE of $0.3056/kWh at
the end of the project period.
However, this study finds that System III fails to reach grid
parity. Adding ESS requires high system costs and financing costs,
and it makes LCOE of the system very high. Though its LCOE
decreases rapidly at the early stage, the difference between System
III and System I is about $0.11/kWh in 2023 when System I reaches
the grid parity condition. At the end of the project period, LCOE
of System III reaches $0.3614/kWh, and it is still $0.04/kWh higher
than that of System III. This result is consistent with Yang
(2010)’s conclusion that solar PV is much less cost effective in a
distributed system. Yang attributed the result in the fact that
many analysts did not amortized all the end-user
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costs and incorrectly considered the cost of $1/W as manufacturing
costs instead of retail installation costs when calculating grid
parity [15].Sustainability 2018, 10, x FOR PEER REVIEW 7 of
14
Figure 2. Yearly LCOEs of the Systems (Unit: $/kWh).
3.2. Sensitivity Analysis
Installing off-grid renewable systems in SIDS can face various
unexpected circumstances and
these issues can increase project costs and threaten project
operations. Thus, the study conducts a
sensitivity analysis to examine how the changes in diesel prices
and discount rates affect the systems’
LCOEs. Table 2 shows the sensitivity analysis conditions considered
in this study.
Table 2. Sensitivity Analysis Conditions.
Sensitivity Analysis
3.2.1. Discount Rate
The project investors require the rate of return on their
investments based on their perception of
the project risk level. Local conditions and risk factors of
installing and operating renewable systems
in SIDS can make project investors to require a higher rate of
return. To reflect it, the study conducts
a sensitivity analysis on discount rate by altering the discount
rate to 10% and 12%. The value of the
discount rate must be carefully assessed because it can influence
the invertor decision towards one
option or another. The value chosen for the discount rate can be
influenced by the investor’s choice
and should be carefully assessed. Thus, we conduct a sensitivity
analysis of discount rates based on
the conservative discount rates assumed by the International Energy
Agency, which are between 10%
and 12% for PV systems [31].
Table 3 and Figure 3 show the LCOEs of the three systems when the
discount rate changes, and
Figure 4 shows when the grid parity condition can be achieved at
the different discount rates. If the
discount rate increases to 10% from 7.8%, LCOEs of the renewable
systems increase slightly while
LCOE of System I decreases to $0.3206/kWh. Still, System II reaches
grid parity, but it is delayed and
occurs in 6.33 years (between 2023 and 2024). System III becomes
more expensive and the LCOE gap
between System III and System I becomes $0.05/kWh at the end of the
project periods. If the discount
Figure 2. Yearly LCOEs of the Systems (Unit: $/kWh).
3.2. Sensitivity Analysis
Installing off-grid renewable systems in SIDS can face various
unexpected circumstances and these issues can increase project
costs and threaten project operations. Thus, the study conducts a
sensitivity analysis to examine how the changes in diesel prices
and discount rates affect the systems’ LCOEs. Table 2 shows the
sensitivity analysis conditions considered in this study.
Table 2. Sensitivity Analysis Conditions.
Sensitivity Analysis
Discount Rate 10% 12% Diesel Price (Real) $0.954 (−10%) $1.166
(+10%) $1.272 (+20%)
3.2.1. Discount Rate
The project investors require the rate of return on their
investments based on their perception of the project risk level.
Local conditions and risk factors of installing and operating
renewable systems in SIDS can make project investors to require a
higher rate of return. To reflect it, the study conducts a
sensitivity analysis on discount rate by altering the discount rate
to 10% and 12%. The value of the discount rate must be carefully
assessed because it can influence the invertor decision towards one
option or another. The value chosen for the discount rate can be
influenced by the investor’s choice and should be carefully
assessed. Thus, we conduct a sensitivity analysis of discount rates
based on the conservative discount rates assumed by the
International Energy Agency, which are between 10% and 12% for PV
systems [31].
Table 3 and Figure 3 show the LCOEs of the three systems when the
discount rate changes, and Figure 4 shows when the grid parity
condition can be achieved at the different discount rates.
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If the discount rate increases to 10% from 7.8%, LCOEs of the
renewable systems increase slightly while LCOE of System I
decreases to $0.3206/kWh. Still, System II reaches grid parity, but
it is delayed and occurs in 6.33 years (between 2023 and 2024).
System III becomes more expensive and the LCOE gap between System
III and System I becomes $0.05/kWh at the end of the project
periods. If the discount rate increases up to 12%, System II
reaches grid parity in 6.95 years (between 2023 and 2024). This
result is supported by the research of Simsek et al. (2018)
demonstrating that debt fraction and discount rate illustrated
significant sensitivities on both LCOE and government cost. By
increasing discount rate from 6% to 12%, the research of Simsek et
al. (2018) also proves that both LCOE and government cost showed an
increasing trend [32]. As the economic feasibility of the project
depends highly on feed-in tariffs concessions, the Maldives’
unstable political and legislative situations could negatively
affect the discount rates of PV and ESS technologies. However, as
the technology matures, and the solar PV markets evolve, the
significance of discount rates will decline over time.
Table 3. LCOEs of the systems when the discount rate changes (Unit:
$/kWh).
Sensitivity Analysis (Discount Rate) 7.8% 10% 12%
LCOEs (System I) 0.3208 0.3206 0.3204 LCOEs (System II) 0.3056
0.3085 0.3113 LCOEs (System III) 0.3614 0.3735 0.3851
Sustainability 2018, 10, x FOR PEER REVIEW 8 of 14
rate increases up to 12%, System II reaches grid parity in 6.95
years (between 2023 and 2024). This
result is supported by the research of Simsek et al. (2018)
demonstrating that debt fraction and
discount rate illustrated significant sensitivities on both LCOE
and government cost. By increasing
discount rate from 6% to 12%, the research of Simsek et al. (2018)
also proves that both LCOE and
government cost showed an increasing trend [32]. As the economic
feasibility of the project depends
highly on feed-in tariffs concessions, the Maldives’ unstable
political and legislative situations could
negatively affect the discount rates of PV and ESS technologies.
However, as the technology matures,
and the solar PV markets evolve, the significance of discount rates
will decline over time.
Table 3. LCOEs of the systems when the discount rate changes (Unit:
$/kWh).
Sensitivity Analysis (Discount Rate) 7.8% 10% 12%
LCOEs (System I) 0.3208 0.3206 0.3204
LCOEs (System II) 0.3056 0.3085 0.3113
LCOEs (System III) 0.3614 0.3735 0.3851
Figure 3. Yearly LCOEs if Discount Rate changes.
Figure 3. Yearly LCOEs if Discount Rate changes.
Sustainability 2018, 10, 4045 9 of 14 Sustainability 2018, 10, x
FOR PEER REVIEW 9 of 14
Figure 4. Grid Parity (Sensitivity Analysis on Discount
Rate).
3.2.2. Diesel Prices
Due to all systems using a large portion of diesel generation, the
changes in diesel prices can
affect LCOEs of the systems significantly. In particular, under the
circumstances of increasing global
diesel prices in recent years, the increase in diesel price can
increase LCOEs of the project.
Table 4 and Figure 5 show the LCOEs of the systems when the diesel
price changes, and Figure
6 shows when the grid parity condition can be achieved at the
different diesel prices. If the diesel
price decreases to $0.954/L, LCOEs of the systems also decrease.
Grid parity of System II can be
reached in 6.6 years (between 2023 and 2024). However, System III
cannot reach grid parity. On the
other hand, if the diesel price increases by 10% and becomes
$1.166/L, grid parity of System II is
reached in 5.11 years (between 2022 and 2023). Also, the LCOE
difference between System III and
System I reduces to $0.035/kWh. If the diesel price further
increases to $1.272/L, the grid parity
condition of System II can be achieved earlier. Grid parity is
achieved in 4.64 years (between 2021
and 2022). This indicates that the project is likely to benefit if
the recent trends of increasing global oil
price continue and the diesel price of the Maldives increases. This
result is supported by research
done by Peerapong and Limmeechokchai who conducted a sensitivity
analysis using variations such
as solar radiations, cost of diesel prices, real interest rates and
load consumptions. The variations of
diesel prices set from $0.9/L to $1.2/L affect NPC, COE, and
renewable shares in the system. The study
Figure 4. Grid Parity (Sensitivity Analysis on Discount
Rate).
3.2.2. Diesel Prices
Due to all systems using a large portion of diesel generation, the
changes in diesel prices can affect LCOEs of the systems
significantly. In particular, under the circumstances of increasing
global diesel prices in recent years, the increase in diesel price
can increase LCOEs of the project.
Table 4 and Figure 5 show the LCOEs of the systems when the diesel
price changes, and Figure 6 shows when the grid parity condition
can be achieved at the different diesel prices. If the diesel price
decreases to $0.954/L, LCOEs of the systems also decrease. Grid
parity of System II can be reached in 6.6 years (between 2023 and
2024). However, System III cannot reach grid parity. On the other
hand, if the diesel price increases by 10% and becomes $1.166/L,
grid parity of System II is reached in 5.11 years (between 2022 and
2023). Also, the LCOE difference between System III and System I
reduces to $0.035/kWh. If the diesel price further increases to
$1.272/L, the grid parity condition of System II can be achieved
earlier. Grid parity is achieved in 4.64 years (between 2021 and
2022). This indicates that the project is likely to benefit if the
recent trends of increasing global oil price continue and the
diesel price of the Maldives increases. This result is supported by
research done by Peerapong and Limmeechokchai who conducted a
sensitivity analysis using variations such as solar radiations,
cost of diesel prices, real interest rates and load consumptions.
The variations of diesel prices set from $0.9/L to $1.2/L affect
NPC, COE, and renewable shares in the system. The study finally
concludes that minimum diesel price should be at least $0.561/L for
the hybrid diesel/PV system with ESS to compete with the
diesel-only existing system [33].
Sustainability 2018, 10, 4045 10 of 14
Table 4. LCOEs of the systems when the diesel price changes (Unit:
(Diesel) $/L; (LCOE) $/kWh).
Sensitivity Analysis (Diesel Price) $0.954 $1.166 $1.272
LCOEs (System I) 0.2907 0.3509 0.3810 LCOEs (System II) 0.2799
0.3314 0.3571 LCOEs (System III) 0.3365 0.3862 0.4111
Sustainability 2018, 10, x FOR PEER REVIEW 10 of 14
finally concludes that minimum diesel price should be at least
$0.561/L for the hybrid diesel/PV system with ESS to compete with
the diesel-only existing system [33].
Table 4. LCOEs of the systems when the diesel price changes (Unit:
(Diesel) $/L; (LCOE) $/kWh).
Sensitivity Analysis (Diesel Price) $0.954 $1.166 $1.272 LCOEs
(System I) 0.2907 0.3509 0.3810 LCOEs (System II) 0.2799 0.3314
0.3571 LCOEs (System III) 0.3365 0.3862 0.4111
Figure 5. Yearly LCOEs when Diesel Price changes.
Figure 5. Yearly LCOEs when Diesel Price changes.
Sustainability 2018, 10, x FOR PEER REVIEW 10 of 14
finally concludes that minimum diesel price should be at least
$0.561/L for the hybrid diesel/PV
system with ESS to compete with the diesel-only existing system
[33].
Table 4. LCOEs of the systems when the diesel price changes (Unit:
(Diesel) $/L; (LCOE) $/kWh).
Sensitivity Analysis (Diesel Price) $0.954 $1.166 $1.272
LCOEs (System I) 0.2907 0.3509 0.3810
LCOEs (System II) 0.2799 0.3314 0.3571
LCOEs (System III) 0.3365 0.3862 0.4111
Figure 5. Yearly LCOEs when Diesel Price changes.
Figure 6. Grid Parity (Sensitivity Analysis on Diesel Price).
Sustainability 2018, 10, 4045 11 of 14
3.2.3. Summary of Sensitivity Analysis
The sensitivity analysis shows the time required to reach grid
parity if the diesel price and discount rate change, and the
detailed results of the sensitivity analysis are shown in Table 5.
Though the analysis indicates that the system design with an ESS
cannot reach grid parity, System II reaches grid parity mostly
within 7 years. If the diesel price goes down and the discount rate
increases, System II requires more time to reach the grid parity as
shown in Table 6. An increase in diesel price benefits the
renewable systems consuming less diesel, and an increase of
discount rate, which means the project is perceived as a riskier
one, can make the renewable systems less attractive.
Table 5. Summary of Results.
LCOEs System I System II System III
@7.8% $1.06 0.3208 0.3056 0.3614 @7.8% $0.954 0.2907 0.2799 0.3365
@7.8% $1.166 0.3509 0.3314 0.3862 @7.8% $1.272 0.3810 0.3571 0.4111
@10% $1.06 0.3206 0.3085 0.3735 @12% $1.06 0.3204 0.3113
0.3851
Table 6. When the Grid Party can be reached (System II).
Sensitivity Analysis $0.954 $1.06 $1.166 $1.272
7.8% 6.6 years 5.77 years 5.11 years 4.64 years 10% 7.35 years 6.33
years 5.58 years 4.95 years 12% 8.25 years 6.95 years 6.01 years
5.35 years
4. Discussion
The study examined whether renewable systems are feasible options
in SIDS based on the case of the Kuda Bandos Island, Maldives.
Also, the study used the LCOE method to find when the grid parity
condition can be met. The case project is to replace the existing
diesel generator to a solar photovoltaic system with ESS and diesel
generator.
Though the project included two types of energy storage systems,
the sensitivity analysis showed that the grid parity of PV with ESS
is hard to be reached within the project lifetime. However, if the
project only uses solar PV and diesel generator, the grid parity
can be reached in 5.77 years, and the renewable system is an
effective solution for replacing the existing diesel generator and
reducing diesel consumption. Moreover, in all cases, the
sensitivity analysis showed that solar PV and diesel generator
(System II) reaches the grid parity condition. Thus, the paper
demonstrates that solar PV already reached the grid parity
condition and became an effective solution for achieving the
renewable target of the Maldives and reducing the heavy dependence
on imported fossil fuel.
The results of the sensitivity analysis indicate that the discount
rate and diesel price are major factors affecting the economic
feasibilities of renewable systems and the grid parity conditions.
The challenges, such as logistics and maintenance issues, of the
SIDS countries caused by their unique characteristics often make
investors perceive the deployment of the off-grid renewable system
in those countries as a risky project. This perception can increase
the discount rate required to evaluate a renewable energy project.
As shown in the sensitivity analysis on the discount rate, a higher
discount rate makes renewable systems which require a huge upfront
investment less attractive, and it delays the periods needed for
achieving the grid parity condition. Thus, a proper assessment of
risk factors of renewable projects and supportive policies for
reducing those risk factors should be considered.
Moreover, the result of the sensitivity analysis on diesel price
provides information about how the introduction of carbon taxes or
environmental taxes can accelerate the grid parity condition in the
Maldives. the Maldives is vulnerable to climate change and focuses
on fuel switching from diesel
Sustainability 2018, 10, 4045 12 of 14
to renewable energy options [34]. Also, tourism is one of the key
parts of the Maldives’ economy. Thus, the country has incentives to
reduce diesel generation, which is the dominant energy system in
the Maldives, emitting greenhouse gases and air pollutants. If the
country introduces environmental taxes or carbon taxes, its impact
is likely to be similar to the sensitivity analysis to an increase
of diesel price. Thus, it can further accelerate the grid parity
condition of PV systems in the Maldives. However, PV with ESS will
remain as a very expensive option. As the sensitivity analysis
indicates, even a 20% increase of diesel price does not bring the
grid parity condition of PV with ESS and diesel generator. This
implies that it will require much longer time to fully eliminate
the diesel generator from the system.
In recent years, the global oil price has been increasing rapidly,
and the Brent Oil price has exceeded $80 per barrel in the late
September 2018 [35]. As shown in the sensitivity analysis on diesel
price, a continued trend of increasing global oil price is likely
to benefit the deployment of renewable systems. Moreover, the
system configuration of the project is pre-determined in the case
project, and the project included high-performance but expensive
batteries in the system configuration. If the trend of increasing
global oil price continues and the optimal system configuration is
considered, the solar photovoltaic with ESS can become a more
attractive option.
Author Contributions: Conceptualization, T.Y.J. and D.K.; Data
curation, J.M. and S.L.; Formal analysis, T.Y.J., D.K., J.M. and
S.L.; Investigation, T.Y.J., D.K., J.M. and S.L.; Methodology,
T.Y.J., D.K., J.M. and S.L.; Project administration, T.Y.J. and
D.K.; Resources, T.Y.J. and D.K.; Software, J.M. and S.L.;
Supervision, T.Y.J. and D.K.; Validation, T.Y.J. and D.K.;
Visualization, J.M.; Writing—original draft, T.Y.J., D.K., J.M. and
S.L.; Writing—review & editing, T.Y.J. and D.K.
Funding: This research was funded by the Korea Institute of Energy
Technology Evaluation and Planning (KETEP) and the Ministry of
Trade, Industry & Energy (MOTIE) of the Republic of Korea (No.
20162010103860).
Acknowledgments: This work was supported by Korea Institute of
Energy Technology Evaluation and Planning (KETEP) grant funded by
the Korea government (MOTIE) (20162010103860, Development and
Demonstration of Multiple Linked ESS for Special Environmental
Areas).
Conflicts of Interest: The authors declare no conflict of
interest.
Acronyms and Abbreviations
SIDS Small Island Developing States PV Photovoltaic ESS Energy
Storage System LCOE Levelized Cost of Energy LIB Lithium-Ion
Battery VRFB Vanadium Redox Flow Battery KETEP The Korea Institute
of Energy Technology Evaluation and Planning MOTIE The Ministry of
Trade, Industry and Energy of the Republic of Korea HOMER Hybrid
Optimization of Multiple Energy Resources CVaR Conditional Value at
Risk MSSP-ABC Multi-stage Stochastic Programming based on
Artificial Bee Colony MO-TE Market Operator Transactive Energy CHP
Combined Heat and Power System PCS Power Conversion System O&M
Operations and Maintenance
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Assumptions and System Components